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---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_organization_task4_fold2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# arabert_cross_organization_task4_fold2
This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3326
- Qwk: -0.0168
- Mse: 1.3108
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
|:-------------:|:------:|:----:|:---------------:|:-------:|:------:|
| No log | 0.0282 | 2 | 5.7271 | 0.0134 | 5.7480 |
| No log | 0.0563 | 4 | 2.8011 | 0.0108 | 2.8128 |
| No log | 0.0845 | 6 | 1.1853 | 0.0747 | 1.1830 |
| No log | 0.1127 | 8 | 0.8362 | 0.0389 | 0.8275 |
| No log | 0.1408 | 10 | 0.8333 | 0.1288 | 0.8213 |
| No log | 0.1690 | 12 | 0.8688 | 0.1267 | 0.8595 |
| No log | 0.1972 | 14 | 0.9519 | 0.1054 | 0.9385 |
| No log | 0.2254 | 16 | 0.9970 | 0.0306 | 0.9822 |
| No log | 0.2535 | 18 | 1.0292 | 0.0258 | 1.0103 |
| No log | 0.2817 | 20 | 1.0334 | -0.0628 | 1.0157 |
| No log | 0.3099 | 22 | 1.0686 | -0.1440 | 1.0532 |
| No log | 0.3380 | 24 | 1.1200 | 0.0189 | 1.0994 |
| No log | 0.3662 | 26 | 1.2013 | 0.0103 | 1.1805 |
| No log | 0.3944 | 28 | 1.2303 | -0.0460 | 1.2082 |
| No log | 0.4225 | 30 | 1.2347 | -0.0420 | 1.2132 |
| No log | 0.4507 | 32 | 1.1787 | -0.0368 | 1.1561 |
| No log | 0.4789 | 34 | 1.1677 | -0.0346 | 1.1449 |
| No log | 0.5070 | 36 | 1.1550 | 0.0020 | 1.1329 |
| No log | 0.5352 | 38 | 1.1940 | -0.0866 | 1.1731 |
| No log | 0.5634 | 40 | 1.1923 | -0.0408 | 1.1735 |
| No log | 0.5915 | 42 | 1.1642 | -0.0408 | 1.1467 |
| No log | 0.6197 | 44 | 1.0921 | -0.0468 | 1.0757 |
| No log | 0.6479 | 46 | 1.0848 | -0.0448 | 1.0687 |
| No log | 0.6761 | 48 | 1.0785 | -0.0317 | 1.0615 |
| No log | 0.7042 | 50 | 1.0877 | 0.0101 | 1.0705 |
| No log | 0.7324 | 52 | 1.1100 | -0.0298 | 1.0927 |
| No log | 0.7606 | 54 | 1.1436 | -0.0217 | 1.1254 |
| No log | 0.7887 | 56 | 1.1970 | -0.0235 | 1.1785 |
| No log | 0.8169 | 58 | 1.2422 | -0.0168 | 1.2238 |
| No log | 0.8451 | 60 | 1.2565 | -0.0168 | 1.2371 |
| No log | 0.8732 | 62 | 1.2821 | -0.0168 | 1.2624 |
| No log | 0.9014 | 64 | 1.3042 | -0.0168 | 1.2840 |
| No log | 0.9296 | 66 | 1.3287 | -0.0168 | 1.3079 |
| No log | 0.9577 | 68 | 1.3368 | -0.0168 | 1.3154 |
| No log | 0.9859 | 70 | 1.3326 | -0.0168 | 1.3108 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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